• Journal of the Korean Society for information Management
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• v.35 no.1
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• pp.13-32
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• 2018

The purpose of this study is to analyze the association among the subject areas of big data research papers. The subject group of the units of analysis was extracted by applying co-citation networks, and the rules of association were analyzed using Apriori algorithm of R program, and visualized using the arulesViz package of R program. As a result of the study, 22 subject areas were extracted and these subjects were divided into three clusters. As a result of analyzing the association type of the subject, it was classified into 'professional type', 'general type', 'expanded type' depending on the complexity of association. The professional type included library and information science and journalism. The general type included politics & diplomacy, trade, and tourism. The expanded types included other humanities, general social sciences, and general tourism. This association networks show a tendency to cite other subject areas that are relevant when citing a subject field, and the library should consider services that use the association for academic information services.

• Journal of Internet of Things and Convergence
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• v.2 no.2
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• pp.21-26
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• 2016

In this paper, it is possible to update the tourist information in real time, on/off-line tour proposes a solution(BBTS) based on a bluetooth beacon can provide tourist information without the need for wireless data network. BBTS consists of a bluetooth based data of the low-power supply system and the beacons and interoperable smart applications. Data supply system consists of the BLE & Beacon Pairing-based / non-pairing data transmission module with integral hardware. Smart application modules that provide indoor location of users information, internal server module and tourist information collection and information guide around comprised of applications. The proposed BBTS is possible that indoor service tourism tourist demand due to utilizing the beacon technology. Outdoor tourist information is designed to be downloaded to the smartphone receives the information received from the beacon APK file to provide services. BBTS system is expected to make a big impact on the smart tourism services industry.

• International Journal of Advanced Culture Technology
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• v.12 no.1
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• pp.158-168
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• 2024

With Wenhai big data SaaS cloud platform.2.0, this study analyzed data of 135 news reports relating to Chinese city Chongqing from Yonhap News Agency and ten South Korean mainstream newspapers from May 1^st, 2018 to September 30^th, 2022. Under the framework of Frame Theory, this research conducted data mining and analysis on how Korean mainstream media shaped city image of Chongqing, what kind of city images were shaped from dimensions of politics, economy, society, culture & sports as well as tourism and whether they are consistent with those in Chinese media. At the last part, discussions and suggestions was made.

• Smart Media Journal
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• v.13 no.9
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• pp.9-17
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• 2024

This study aims to analyze the current status of smart tourism in various regions. To achieve this, 599 news articles containing the keyword 'smart tourism' were collected from national daily newspapers in the BigKinds database, covering the period from January 2014 to June 2024. The collected data was subject to topic modeling based on location, and network analysis was performed using the keyword frequencies in each topic. The topic modeling results identified six major topics: 'Jeju,' 'Incheon,' 'Daegu_Busan_Ulsan,' 'Gyeongju,' 'Suwon,' and 'Yangyang.' It was found that the development of smart tourism in all these regions is centered around tourism projects led by government and local authorities. The network analysis results revealed that 'platform' and 'content' are key keywords related to smart tourism technology across all topics, indicating that these concepts are interconnected to provide services to individual tourists. The findings of this study are expected to provide valuable information for formulating policies and strategies to promote smart tourism in various regions and contribute to the realization of sustainable smart tourism.

• Journal of the Korean Data and Information Science Society
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• v.26 no.2
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• pp.409-418
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• 2015

With the development of mobile devices and Internet, information exchange has actively been made through SNS and Blogs. Blogs are widely used as a space where people share their experience after their visit to tourist attractions. We propose a method of recommending associated tourist attractions based on tourists' opinions using issue analysis, association analysis, and sentimental analysis for various online reviews including news in order to help to develop tour products and policies. The result shows that north area of Chungbuk province has been selected as issue attractions, and associated attractions/keywards have been identified for given well-known attraction. Positive/negative opinion for review texts has been analyzed and user can grasp the reason for the sentiments. Multidimensional analysis technique has been integrated to derive additional sophisticated insights and various policy proposal for smart tourism.

• Journal of Smart Tourism
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• v.4 no.2
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• pp.5-14
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• 2024

This study explores the transformative potential of machine learning (ML) and ML-driven data analytics in the hospitality industry. It provides a comprehensive overview of this emerging method, from explaining ML's origins to introducing the evolution of ML-driven data analytics in the hospitality industry. The present study emphasizes the shift embodied in ML, moving from explicit programming towards a self-learning, adaptive approach refined over time through big data. Meanwhile, social media analytics has progressed from simplistic metrics deriving nuanced qualitative insights into consumer behavior as an industry-specific example. Additionally, this study explores innovative applications of these innovative technologies in the hospitality sector, whether in demand forecasting, personalized marketing, predictive maintenance, etc. The study also emphasizes the integration of ML and social media analytics, discussing the implications like enhanced customer personalization, real-time decision-making capabilities, optimized marketing campaigns, and improved fraud detection. In conclusion, ML-driven hospitality data analytics have become indispensable in the strategic and operation machinery of contemporary hospitality businesses. It projects these technologies' continued significance in propelling data-centric advancements across the industry.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.206-211
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• 2022

As the level of consumption is improved and cultural life is pursued, the consumer's consciousness structure is rapidly changing, and the demand for product selection level, variety, and quality is becoming more diverse. The restaurant economy is falling due to the prolonged COVID-19, the economic recession, income decline, and changes in population structure and lifestyle, but the Meal- kit market is growing rapidly. This study aims to identify the consumer perception of Meal-kit, which is rapidly growing as an alternative to existing meals in the fields of dining out, food, and distribution due to the development of technology and social environment using big data. As a result of the analysis, the keywords with the highest frequency of appearance were in the order of Meal-kit, Cooking, Product, Launching, and Market and were divided into 8 groups through the CONCOR analysis. We want to identify consumer trends related to the key keywords of Meal-kit, present effective data related to Meal-kit demand for Meal-kit specialized companies, and provide implications for establishing marketing strategies for differentiated competitive advantage.

• Journal of the Korean Dietetic Association
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• v.30 no.4
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• pp.227-239
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• 2024

This study aimed to analyze the factors influencing the adaptation of novice nutrition teachers through big data analysis and to propose strategies for enhancing this process. Data were collected from internet portals using the keywords 'novice nutrition teacher' and 'nutrition teacher' from May 25, 2021, to May 25, 2024. Text mining techniques, including frequency analysis, semantic network analysis, and CONvergence of iterated CORrelations (CONCOR) analysis, were employed. Key terms such as 'teacher', 'nutrition', 'career', 'school', and 'school meals' exhibited high frequency and centrality, indicating the multifaceted roles of novice nutrition teachers and the need for increased support. Excessive workload and stress related to school meal management negatively impacted adaptation, highlighting the need for systematic management and capacity-building training programs. Mentoring and consulting systems played a crucial role in enhancing professional development, leading to better adaptation and higher job satisfaction. Additionally, stress and anxiety during the appointment preparation process were significant factors influencing adaptation, suggesting the need for improvements in the training curriculum at teacher education institutions. These findings provide valuable insights for developing policies to support the adaptation of novice nutrition teachers.

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.1
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• pp.12-28
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• 2024

This study aims to identify the trend of changes in tourist floating population before and after COVID-19 in major tourist destinations in Jeju Island through spatial analysis. Seongsan-eup and Andeok-myeon in Jeju Island were selected as the research area, and the research period was set at 1 year before and 2 years after the COVID-19 outbreak. For the analysis, mobile floating population data was refined and processed to calculate floating population distribution and floating population increase/decrease data. This was converted into spatial data and an overlay analysis was performed with location data of major tourist attractions. As a result of the analysis, it was confirmed that the floating population of indoor tourist attractions and small facilities decreased immediately after COVID-19, and that in open coastal areas or large facilities, the floating population decreased less or actually increased. In conclusion, in tourism development, it is necessary to identify changes in floating population according to the characteristics of tourist facilities, and it is necessary to develop tourism facilities and strategies that can respond to risk situations such as pandemics when developing tourist destinations.

• Culinary science and hospitality research
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• v.23 no.6
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• pp.27-35
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• 2017

The purpose of this study was to examine the causal relationship among restaurant selection attributes and customer satisfaction and recommendation tastes for young people in their twenties who use tickets for Rail-ro. Data collection was conducted to utilize questionnaire survey with online and offline distribution. The collected data were analyzed using a statistical program SPSS 21.0 with frequency analysis, reliability analysis, factor analysis, and regression analysis. The results of the study showed that Internet search is the most common source of information about restaurants during the trip, and restaurant choice attributes have an important impact on customer satisfaction, food quality, employee service and reputation, but hygiene did not have a big effect on customer satisfaction. In addition, customer satisfaction has a significant effect on recommendation intention. Concluding the results from this study, it investigated the significant attributes for customers selection of restaurants and provide meaningful advice for market managers to make useful marketing strategies to attract more clients and augment economic benefits.